This core will support the production of computer based forecasts and simulations of changes in the health and functioning of the U.S. elderly population and estimate the cost differentials associated with changes in those forecasts due to the use of different assumptions. The empirical basis of these forecasts will initially be the changes in functional status and dimensions and mortality assessed in the 1982, 1984, 1989, 1994, and 1999 NLTCS. The model is designed so that the parameters of the health process can be made functions of different types of non-health inputs generated by modeling effects in various of the specific research projects. Thus, models of economic effects on health will be generated in Projects 2, 3 and 4. Project 1 will deal with the methodological issues involved in constructing the mathematical interfaces of the health forecasting model with the other models developed, and empirically calibrated, in the various projects. One of the major issues to be dealt with in the sub-projects is how research investment relates to the rate of adoption, and efficacy of, clinical innovations. There is relatively little direct data on this relation, That is, it is possible to derive estimates of the amount spent on specific types of research, to derive estimates of the amount spent on purchasing specific clinical services made possible by that research, and to derive estimates of how much health is changed by various levels of health spending. There is little data directly relating research investments to changes in health for specific individuals however. Thus, we propose to use the available data and link in a mathematically consistent structure with inputs from experts on biomedical research and from experts on the clinical application of specific technologies. We will examine the sensitivity of health outcomes to such investments taking account of the evident degree of stochastic and construct uncertainty. That effort will help in identifying types and sources of additional evidence that may help to resolve some of this uncertainty.